Gene expression profiling of clinical stages II and III breast cancer

Clinical stage (CS) is an established indicator of breast cancer outcome. In the present study, a cDNA microarray platform containing 692 genes was used to identify molecular differences between CSII and CSIII disease. Tumor samples were collected from patients with CSII or CSIII breast cancer, and normal breast tissue was collected from women without invasive cancer. Seventy-eight genes were deregulated in CSIII tumors and 22 in CSII tumors when compared to normal tissue, and 20 of them were differentially expressed in both CSII and CSIII tumors. In addition, 58 genes were specifically altered in CSIII and expression of 6 of them was tested by real time RT-PCR in another cohort of patients with CSII or CSIII breast cancer and in women without cancer. Among these genes, MAX, KRT15 and S100A14, but not APOBEC3G or KRT19, were differentially expressed on both CSIII and CSII tumors as compared to normal tissue. Increased HMOX1 levels were detected only in CSIII tumors and may represent a molecular marker of this stage. A clear difference in gene expression pattern occurs at the normal-to-cancer transition; however, most of the differentially expressed genes are deregulated in tumors of both CS (II and III) compared to normal breast tissue.

A multicentre randomized controlled trial of an empowerment-inspired intervention for adolescents starting continuous subcutaneous insulin infusion : a study protocol

Background. Continuous subcutaneous insulin infusion (CSII) treatment among children with type 1 diabetes is increasing in Sweden. However, studies evaluating glycaemic control in children using CSII show inconsistent results. Omitting bolus insulin doses using CSII may cause reduced glycaemic control among adolescents. The distribution of responsibility for diabetes self-management between children and parents is often unclear and needs clarification. There is much published support for continued parental involvement and shared diabetes management during adolescence. Guided Self-Determination (GSD) is an empowerment-based, person-centred, reflection and problem solving method intended to guide the patient to become self-sufficient and develop life skills for managing difficulties in diabetes self-management. This method has been adapted for adolescents and parents as Guided Self-Determination-Young (GSD-Y). This study aims to evaluate the effect of an intervention with GSD-Y in groups of adolescents starting on insulin pumps and their parents on diabetes-related family conflicts, perceived health and quality of life (QoL), and metabolic control. Here, we describe the protocol and plans for study enrolment. Methods. This study is designed as a randomized, controlled, prospective, multicentre study. Eighty patients between 12-18 years of age who are planning to start CSII will be included. All adolescents and their parents will receive standard insulin pump training. The education intervention will be conducted when CSII is to be started and at four appointments in the first 4 months after starting CSII. The primary outcome is haemoglobin A1c levels. Secondary outcomes are perceived health and QoL, frequency of blood glucose self-monitoring and bolus doses, and usage of carbohydrate counting. The following instruments will be used to evaluate perceived health and QoL: Disabkids, 'Check your health', the Diabetes Family Conflict Scale and the Swedish Diabetes Empowerment Scale. Outcomes will be evaluated within and between groups by comparing data at baseline, and at 6 and 12 months after starting treatment. Results and discussion. In this study, we will assess the effect of starting an insulin pump together with the model of Guided Self-Determination to determine whether this approach leads to retention of improved glycaemic control, QoL, responsibility distribution and reduced diabetes-related conflicts in the family. Trial registration: Current controlled trials: ISRCTN22444034

Dispositivi per l'assistenza "home care" dei pazienti diabetici

L’ obiettivo della tesi proposta è volto ad illustrare come la malattia diabetica può essere gestita a livello domiciliare attraverso dispositivi di monitoraggio della glicemia sempre più innovativi. La malattia diabetica è un disturbo metabolico che ha come manifestazione principale un aumento del livello di zucchero nel sangue (glicemia) dovuto ad una ridotta produzione di insulina, l’ormone secreto dal pancreas per utilizzare gli zuccheri e gli altri componenti del cibo e trasformarli in energia. È una delle patologie croniche a più ampia diffusione nel mondo, in particolare nei Paesi industrializzati, e costituisce una delle più rilevanti e costose malattie sociali della nostra epoca, soprattutto per il suo carattere di cronicità, per la tendenza a determinare complicanze nel lungo periodo e per il progressivo spostamento dell’insorgenza verso età giovanili. Le tecnologie applicate alla terapia del diabete hanno consentito negli ultimi vent’anni di raggiungere traguardi molto importanti, soprattutto per quanto riguarda l’ottimizzazione del controllo assiduo dei valori glicemici cercando di mantenerli il più costante possibile e ad un livello simile a quello fisiologico. La comunicazione medico-paziente è stata rivoluzionata dalla telemedicina che, offrendo la possibilità di una comunicazione agevole, permette di ottimizzare l’utilizzo dei dati raccolti attraverso l’automonitoraggio glicemico e di facilitare gli interventi educativi. I glucometri, che misurano la glicemia ‘capillare’, insieme ai microinfusori, sistemi di erogazione dell’insulina sia in maniera continua (fabbisogno basale), che ‘a domanda’ (boli prandiali), hanno sostanzialmente modificato l’approccio e la gestione del diabete da parte del medico, ma soprattutto hanno favorito al paziente diabetico un progressivo superamento delle limitazioni alle normali attività della vita imposte dalla malattia. Con il monitoraggio continuo della glicemia 24 ore su 24 infatti, si ha avuto il vantaggio di avere a disposizione un elevato numero di misurazioni puntiformi nell’arco della giornata attraverso sensori glicemici, che applicati sulla pelle sono in grado di ‘rilevare’ il valore di glucosio a livello interstiziale, per diversi giorni consecutivi e per mezzo di un trasmettitore wireless, inviano le informazioni al ricevitore che visualizza le letture ottenute dal sensore. In anni recenti, il concetto di SAP (Sensor-Augmented Insulin Pump) Therapy, è stato introdotto a seguito di studi che hanno valutato l’efficacia dell’utilizzo della pompa ad infusione continua di insulina (CSII, continuous subcutaneous insulin infusion) associato ai sistemi di monitoraggio in continuo della glicemia (CGM, continuous glucose monitoring) per un significativo miglioramento del controllo glicemico e degli episodi sia di ipoglicemia sia di iperglicemia prolungata. Oggi, grazie ad una nuova funzione è possibile interrompere automaticamente l’erogazione di insulina da parte del microinfusore quando la glicemia, rilevata dal sensore, scende troppo velocemente e raggiunge un limite di allarme. Integrare lettura della glicemia, infusione e sospensione automatica dell’erogazione di insulina in caso di ipoglicemia ha ovviamente aperto la porta al pancreas artificiale.

Continuous subcutaneous insulin infusion therapy: effects on quality of life

To compare the diabetes-specific quality of life in subjects with type 1 diabetes treating their diabetes with multiple daily injections (MDI) to that of subjects on continuous subcutaneous insulin infusion (CSII).

Establishing glycaemic control with continuous subcutaneous insulin infusion in children and adolescents with type 1 diabetes: experience of the PedPump Study in 17 countries

AIMS/HYPOTHESIS: To assess the use of paediatric continuous subcutaneous infusion (CSII) under real-life conditions by analysing data recorded for up to 90 days and relating them to outcome. METHODS: Pump programming data from patients aged 0-18 years treated with CSII in 30 centres from 16 European countries and Israel were recorded during routine clinical visits. HbA(1c) was measured centrally. RESULTS: A total of 1,041 patients (age: 11.8 +/- 4.2 years; diabetes duration: 6.0 +/- 3.6 years; average CSII duration: 2.0 +/- 1.3 years; HbA(1c): 8.0 +/- 1.3% [means +/- SD]) participated. Glycaemic control was better in preschool (n = 142; 7.5 +/- 0.9%) and pre-adolescent (6-11 years, n = 321; 7.7 +/- 1.0%) children than in adolescent patients (12-18 years, n = 578; 8.3 +/- 1.4%). There was a significant negative correlation between HbA(1c) and daily bolus number, but not between HbA(1c) and total daily insulin dose. The use of <6.7 daily boluses was a significant predictor of an HbA(1c) level >7.5%. The incidence of severe hypoglycaemia and ketoacidosis was 6.63 and 6.26 events per 100 patient-years, respectively. CONCLUSIONS/INTERPRETATION: This large paediatric survey of CSII shows that glycaemic targets can be frequently achieved, particularly in young children, and the incidence of acute complications is low. Adequate substitution of basal and prandial insulin is associated with a better HbA(1c).

A reduction in severe hypoglycaemia in type 1 diabetes in a randomized crossover study of continuous intraperitoneal compared with subcutaneous insulin infusion

Continuous intraperitoneal insulin infusion (CIPII) with the DiaPort system using regular insulin was compared to continuous subcutaneous insulin infusion (CSII) using insulin Lispro, to investigate the frequency of hypoglycemia, blood glucose control, quality of life, and safety.

An insulin infusion advisory system for type 1 diabetes patients based on non-linear model predictive control methods

In this paper, an Insulin Infusion Advisory System (IIAS) for Type 1 diabetes patients, which use insulin pumps for the Continuous Subcutaneous Insulin Infusion (CSII) is presented. The purpose of the system is to estimate the appropriate insulin infusion rates. The system is based on a Non-Linear Model Predictive Controller (NMPC) which uses a hybrid model. The model comprises a Compartmental Model (CM), which simulates the absorption of the glucose to the blood due to meal intakes, and a Neural Network (NN), which simulates the glucose-insulin kinetics. The NN is a Recurrent NN (RNN) trained with the Real Time Recurrent Learning (RTRL) algorithm. The output of the model consists of short term glucose predictions and provides input to the NMPC, in order for the latter to estimate the optimum insulin infusion rates. For the development and the evaluation of the IIAS, data generated from a Mathematical Model (MM) of a Type 1 diabetes patient have been used. The proposed control strategy is evaluated at multiple meal disturbances, various noise levels and additional time delays. The results indicate that the implemented IIAS is capable of handling multiple meals, which correspond to realistic meal profiles, large noise levels and time delays.

Artificial pancreas using a personalized rule-based controller achieves overnight normoglycemia in patients with type 1 diabetes

Objective: This study assessed the efficacy of a closed-loop (CL) system consisting of a predictive rule-based algorithm (pRBA) on achieving nocturnal and postprandial normoglycemia in patients with type 1 diabetes mellitus (T1DM). The algorithm is personalized for each patient’s data using two different strategies to control nocturnal and postprandial periods. Research Design and Methods: We performed a randomized crossover clinical study in which 10 T1DM patients treated with continuous subcutaneous insulin infusion (CSII) spent two nonconsecutive nights in the research facility: one with their usual CSII pattern (open-loop [OL]) and one controlled by the pRBA (CL). The CL period lasted from 10 p.m. to 10 a.m., including overnight control, and control of breakfast. Venous samples for blood glucose (BG) measurement were collected every 20 min. Results: Time spent in normoglycemia (BG, 3.9–8.0 mmol/L) during the nocturnal period (12 a.m.–8 a.m.), expressed as median (interquartile range), increased from 66.6% (8.3–75%) with OL to 95.8% (73–100%) using the CL algorithm (P<0.05). Median time in hypoglycemia (BG, <3.9 mmol/L) was reduced from 4.2% (0–21%) in the OL night to 0.0% (0.0–0.0%) in the CL night (P<0.05). Nine hypoglycemic events (<3.9 mmol/L) were recorded with OL compared with one using CL. The postprandial glycemic excursion was not lower when the CL system was used in comparison with conventional preprandial bolus: time in target (3.9–10.0 mmol/L) 58.3% (29.1–87.5%) versus 50.0% (50–100%). Conclusions: A highly precise personalized pRBA obtains nocturnal normoglycemia, without significant hypoglycemia, in T1DM patients. There appears to be no clear benefit of CL over prandial bolus on the postprandial glycemia

Páncreas artificial basado en un controlador Smith paramétrico

La diabetes mellitus es una enfermedad que se caracteriza por la nula o insuficiente producción de insulina, o la resistencia del organismo a la misma. La insulina es una hormona que ayuda a que la glucosa llegue a los tejidos periféricos y al sistema nervioso para suministrar energía. Actualmente existen dos tipos de terapias aplicada en tejido subcutáneo: mediante inyección múltiple realizada con plumas, y la otra es mediante infusión continua de insulina por bomba (CSII). El mayor problema de esta terapia son los retardos por la absorción, tanto de los carbohidratos como de la insulina, y los retardos introducidos por el sensor subcutáneo de glucosa que mide la glucosa del líquido intersticial, lo deseable es controlar la glucosa en sangre. Para intentar independizar al paciente de su enfermedad se está trabajando en el desarrollo del páncreas endocrino artificial (PEA) que dotaría al paciente de una bomba de insulina, un sensor de glucosa y un controlador, el cual se encargaría de la toma de decisiones de las infusiones de insulina. Este proyecto persigue el diseño de un regulador en modo de funcionamiento en CL, con el objetivo de conseguir una regulación óptima del nivel de glucosa en sangre. El diseño de dicho regulador va a ser acometido utilizando la teoría del control por modelo interno (IMC). Esta teoría se basa en la idea de que es necesario realimentar la respuesta de un modelo aproximado del proceso que se quiere controlar. La salida del modelo, comparada con la del proceso real nos da la incertidumbre del modelo de la planta, frente a la planta real. Dado que según la teoría del modelo interno, estas diferencias se dan en las altas frecuencias, la teoría IMC propone un filtro paso bajo como regulador en serie con la inversa del modelo de la planta para conseguir el comportamiento deseado. Además se pretende implementar un Predictor Smith para minimizar los efectos del retardo de la medida del sensor. En el proyecto para conseguir la viabilidad del PEA se ha adaptado el controlador IMC clásico utilizando las ganancias estáticas de un modelo de glucosa, a partir de la ruta subcutánea de infusión y la vía subcutánea de medida. El modo de funcionamiento del controlador en SCL mejora el rango de normoglucemia, necesitando la intervención del paciente indicando anticipadamente el momento de las ingestas al controlador. El uso de un control SCL con el Predictor de Smith mejora los resultados pues se añade al controlador una variable sobre las ingestas con la participación del paciente. ABSTRACT. Diabetes mellitus is a group of metabolic diseases in which a person has high blood sugar, due to the body does not produce enough insulin, or because cells do not respond to the insulin produced. The insulin is a hormone that helps the glucose to reach to outlying tissues and the nervous system to supply energy. There are currently two types of therapies applied in subcutaneous tissue: the first one consists in using the intensive therapy with an insulin pen, and the other one is by continuous subcutaneous insulin infusion (CSII). The biggest problems of this therapy are the delays caused by the absorption of carbohydrates and insulin, and the delays introduced by the subcutaneous glucose sensor that measures glucose from interstitial fluid, it is suitable to control glucose blood. To try to improve these patients quality of life, work is being done on the development of an artificial endocrine pancreas (PEA) consisting of a subcutaneous insulin pump, a subcutaneous glucose sensor and an algorithm of glucose control, which would calculate the bolus that the pump would infuse to patient. This project aims to design a controller for closed-loop therapy, with the objective of obtain an optimal regulation of blood glucose level. The design of this controller will be formed using the theory of internal model control (IMC). This theory is based on the uncertainties given by a model to feedback the system control. Output model, in comparison with the actual process gives the uncertainty of the plant model, compared to the real plant. Since the theory of the internal model, these differences occur at high frequencies, the theory proposes IMC as a low pass filter regulator in series with the inverse model of the plant to get the required behavior. In addition, it will implement a Smith Predictor to minimize the effects of the delay measurement sensor. The project for the viability of PEA has adapted the classic IMC controller using the gains static of glucose model from the subcutaneous infusion and subcutaneous measuring. In simulation the SemiClosed-Loop controller get on the normoglycemia range, requiring patient intervention announce the bolus priming connected to intakes. Using an SCL control with the Smith Predictor improves the outcome because a variable about intakes is added to the controller through patient intervention.